Familiarize yourself with commands that can be used to do morphological processing of binary images using the Image Processing toolbox in Matlab (imerode, bwhitmiss, bwpack, bwunpack, imclose, imdilate, imopen, strel, etc.) Reproduce the Example illustrated in Figure 9.11 using dilations and erosions only first using the same structuring element B as shown (show the difference image between the original and the processed image). Repeat the processing using a different size/shape structuring elements to obtain a significantly different result (show the difference image between both of the processed images).

Instead of proving the expressions, use a small binary image to verify them using Matlab.

9.15 Prove the validity of the following expressions:

(a) A B is a subset (subimage) of A

(b) If C is a subset of D, then C B is a subset of D B

(c) (A B) B = A B

Morphological Image Processing for Binary Images Familiarize yourself with commands that can be used to do morphological processing of binary images using the Image Processing toolbox in Matlab (imerode, bwhitmiss, bwpack, bwunpack, imclose, imdilate, imopen, strel, etc.) Reproduce the Example illustrated in Figure 9.11 using dilations and erosions only first using the same structuring element B as shown (show the difference image between the original and the processed image). Repeat the processing using a different size/shape structuring elements to obtain a significantly different result (show the difference image between both of the processed images) The original image is in the file: Fig0911(a)(noisy_fingerprint).tif 9.15; Instead of proving the expressions, use a SMALL binary image to verify them using Matlab 9.15 Prove the validity of the following expressions: x(a) A o B is a subset (subimage) of A. (b) If C is a subset of D, then C o B is a subset of D o B. (c) (A+ B) A+ B. Morphological Image Processing for Binary Images Familiarize yourself with commands that can be used to do morphological processing of binary images using the Image Processing toolbox in Matlab (imerode, bwhitmiss, bwpack, bwunpack, imclose, imdilate, imopen, strel, etc.) Reproduce the Example illustrated in Figure 9.11 using dilations and erosions only first using the same structuring element B as shown (show the difference image between the original and the processed image). Repeat the processing using a different size/shape structuring elements to obtain a significantly different result (show the difference image between both of the processed images) The original image is in the file: Fig0911(a)(noisy_fingerprint).tif 9.15; Instead of proving the expressions, use a SMALL binary image to verify them using Matlab 9.15 Prove the validity of the following expressions: x(a) A o B is a subset (subimage) of A. (b) If C is a subset of D, then C o B is a subset of D o B. (c) (A+ B) A+ B